Date and Time
The course will be held online on March 4th and March 5th, from 9 am to 1 pm.
Prerequisites
- Basic C/C++ competency, including familiarity with variable types, loops, conditional statements, functions, and array manipulations
- No previous knowledge of CUDA programming is assumed
- A free NVIDIA developer account is required to access the course material. Please register before the training at https://courses.nvidia.com/join/.
Learning Objectives
At the conclusion of the workshop, participants will have an understanding of the fundamental tools and techniques for GPU- accelerating C/C++ applications with CUDA and be able to:
- Write code to be executed by a GPU accelerator
- Expose and express data and instruction-level parallelism in C/C++ applications using CUDA
- Utilize CUDA-managed memory and optimize memory migration using asynchronous prefetching
- Leverage command-line and visual profilers to guide your work
- Utilize concurrent streams for instruction-level parallelism
- Write GPU-accelerated CUDA C/C++ applications, or refactor existing CPU-only applications, using a profile-driven approach
Certification
Upon successful completion of the assessment at the end of the second day, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.
Structure
Module 1 -- Accelerating Applications with CUDA C/C++
- Writing, compiling, and running GPU code
- Controlling the parallel thread hierarchy
- Allocating and freeing memory for the GPU
Module 2 -- Managing Accelerated Application Memory with CUDA C/C++
- Profiling CUDA code with the command-line profiler
- Details on unified memory
- Optimizing unified memory management
Module 3 -- Asynchronous Streaming and Visual Profiling for Accelerated Applications with CUDA C/C++
- Profiling CUDA code with NVIDIA Nsight Systems
- Using concurrent CUDA streams
Program
The program can be found here.
Language
The course will be held in English.
Instructor
Dr. Sebastian Kuckuk, certified NVIDIA DLI Ambassador.
The course is co-organised by NHR@FAU and the NVIDIA Deep Learning Institute (DLI).
Prices and Eligibility
The course is co-organized by EUMaster4HPC. Students of the EUMaster4HPC program at a participating university are given priority.
The remaining seats are open for other students and members of universities participating in the EUMaster4HPC program.
Withdrawal Policy
Please only register for the course if you are really going to attend. No-shows will be blacklisted and excluded from future events. If you want to withdraw your registration, please send e-mail to sebastian.kuckuk@fau.de.
